Term of Award
Master of Science, Electrical Engineering
Document Type and Release Option
Thesis (restricted to Georgia Southern)
Copyright Statement / License for Reuse
This work is licensed under a Creative Commons Attribution 4.0 License.
Department of Electrical and Computer Engineering
Rami J Haddad
Committee Member 1
Committee Member 2
The human brain can be referred to as a super micro-controller, capable of managing all forms of activities in the human body. The brain is composed of millions of neurons (motor/sensory), which helps it carry out multiple activities at the same time. The neurons act like electrical networks that transport signals to and from different parts of the body. In a nutshell, every part of the body is connected by neurons. These neurons help in carrying signals from any parts of the body to the brain, while the brain, in return, makes logical decisions based on the information received. Brain activities could be monitored and recorded for analysis purposes by the technology of human-computer interfacing called brain-computer interface (BCI). However, other technologies do exist that could perform this same function. BCI involves the use of peripheral components, mostly worn on the head, for light application usage. Electroencephalography (EEG) is highly efficient in recording brain activities using electrodes attached to the human scalp. These electrodes measure ionic current signals within the associated brain neurons. These brain signals could range from 0.1 Hz to over 100 Hz frequencies and could be classified as alpha, beta, gamma, delta, and theta. The goal of this research is to study and show how the brain reacts to any distraction effects, as distracted driving has contributed to a large percentage of accidents on the highways. Out of all the brain waves, the alpha waves would be our primary focus for this project, in addition to other factors such as steering angle deviation and velocity deviation that would also be considered. Drivers would be subjected to driving under a distraction effect, which is an advertisement billboard, with the performance parameters recorded. They would also drive under normal conditions, that is, with no distraction effect, with their performance parameters recorded as well. The treatment effect will be assessed using one-way ANOVA analysis, Tukey pairwise comparisons, and the significance and relationship between this distraction effect and all these factors, such as alpha wave, steering angle deviation, and velocity deviation.
Sadeeq, Lanre Gbenga, "Investigating Driving Distraction Using Electroencephalography (EEG)" (2020). Electronic Theses and Dissertations. 2112.
Research Data and Supplementary Material